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Authors: Konstantinos Makantasis 1 ; Nikolaos Doulamis 2 and Athanasios Voulodimos 2

Affiliations: 1 Technical University of Crete, Greece ; 2 National Technical University of Athens, Greece

Keyword(s): Deep Learning, Building Recognition, Urban Cultural Heritage.

Abstract: Automatic detection and recognition of specific types of urban buildings is extremely important for a variety of applications ranging from outdoor urban reconstruction to navigation. In this paper we propose a system for the automatic detection and recognition of urban buildings. Most of the existing work relies on the exploitation of handcrafted features for recognizing buildings. However, due to their complex structure it is rarely a priori known which features are important for the recognition task. Our method overcomes this drawback by exploiting a deep learning framework, based on convolutional neural networks, which automatically construct highly descriptive features directly from raw data. We evaluate the performance of our method on the recognition of half-timbered framed buildings in Calw city in Germany.

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Paper citation in several formats:
Makantasis, K.; Doulamis, N. and Voulodimos, A. (2017). Recognizing Buildings through Deep Learning: A Case Study on Half-timbered Framed Buildings in Calw City. In Proceedings of the 12th International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications - Volume 5: CVICG4CULT; ISBN 978-989-758-226-4; ISSN 2184-4321, SciTePress, pages 444-450. DOI: 10.5220/0006347204440450

@conference{cvicg4cult17,
author={Konstantinos Makantasis. and Nikolaos Doulamis. and Athanasios Voulodimos.},
title={Recognizing Buildings through Deep Learning: A Case Study on Half-timbered Framed Buildings in Calw City},
booktitle={Proceedings of the 12th International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications - Volume 5: CVICG4CULT},
year={2017},
pages={444-450},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0006347204440450},
isbn={978-989-758-226-4},
issn={2184-4321},
}

TY - CONF

JO - Proceedings of the 12th International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications - Volume 5: CVICG4CULT
TI - Recognizing Buildings through Deep Learning: A Case Study on Half-timbered Framed Buildings in Calw City
SN - 978-989-758-226-4
IS - 2184-4321
AU - Makantasis, K.
AU - Doulamis, N.
AU - Voulodimos, A.
PY - 2017
SP - 444
EP - 450
DO - 10.5220/0006347204440450
PB - SciTePress

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